FanPost

How to be fair to Trevor Timmins?

Whenever the team goes through bad times, you can hear the rattling of pikes and forks as the mob marches towards la Place du Centenaire. We want heads to roll. And Trevor Timmins is always a crowd favorite on these special occasions. Because, you know, after all these years, there can’t be any excuses left. Sure, drafting is not an exact science, but 2003! Your kids weren’t even born! If he was really good, after all these years, we’d know. Right?

The thing is, there is only one draft each year. By nature we have only a small sample to work with when we evaluate the success of a head scout. Even after 15 years the number of picks is around a hundred. When you categories, because you can’t compare top five picks with end of first round picks and 2nd round picks, etc, the sample gets thin pretty fast.

A few years ago I read a book written by mathematician Leonard Mlodinow called The drunkard's walk, how randomness rules our lives. Mlodinow gives a lot of examples of how we are wrong about things. A lot of those examples are about pro sport drafting. "Deciding just how much of an outcome is due to skill and how much to luck is not a no-brainer. Random events often come like raisins in a box of cereal - in groups, streaks and clusters. And although Fortune is fair in potentiality, she is not fair in outcomes." A Hollywood company fires one of its producers (another small sample over many years kind of job) because her last four movies were disappointing at the box office. A few years later you realise that the last three movies she worked on, and that were still in the pipeline when you fired her, turned out to be huge successes. Oups.

So should we just shut up and suffer then? What if Timmins really is bad? Should we give up all hopes to see the cup in Montreal in our lifetime because of sample size? Of course we won’t shut up. Journalists have to write articles week after week. Panelists have to talk and talk. And fans… well you know fans. So we still want to judge but can we be a little fairer about it. Can we use the numbers and try to remove some of the noise. That is what I will try to do.

Has Shania Twain would sing it: "So you consecutively drafted Fleury, Malkin, Crosby and Stall, in the top 2, and they won the cup? That don’t impress me much! So you got the rings but have you got the touch?" And how would I know if you’re actually alright? Getting the obvious star doesn’t make you a good head scout. One head scout gets to pick third in 2003 while another gets to do it in 2012. Not the same thing at all. What tells them apart is the potential available when they make the pick. So I’m thinking evaluating drafts is not so much about who picked the best player but more like who didn't let go of a huge opportunity. The scale should reward and punish. I decided to try to test that and realised that hockeydb.com’s draft tables can be copied and pasted in a spreadsheet. So I did that for drafts from 2003 (beginning for Timmins) to 2016 (later drafts are not telling enough for now) on 2021-11-11 (yes data has to be time stamped).

First equalize by position

To analyse by data you need to score things. A good way to score a player drafted is by game played and points (goals + assists). You shouldn’t be penalized for picking a goalie or a defenseman though. I decided to score like this:

  • Forwards by games played + points

  • Defensemen by games played + 2 * points

  • Goalies by game played * a factor (3.286) to get the average similar to that of other players (wins and loss is not in that database and anyway this works fine)

Next, evaluate potential

So each pick is now given a score. But they also have a potential; that is the sum of all the scores still available at that point in the draft. For example, picking Sidney Crosby gives you a score of 2 365 (2021-11-11). But, since he is the first pick of that draft, he also comes with a huge potential, the sum of all that draft: 51 123. For the second pick Crosby is no longer available so the potential of that pick drops by 2 365 to 48 758.

Calculate a Scouting Rating

Each time a team picks, it scores points which add up. That team also accumulates the potentials associated with the pick they made. At the end you have a sum of scores and a sum of potentials for the period of your database. The Scouting Rating is total score/ total potential. I multiplied by 10 000 and rounded to get a nice 3 digit rating.

So if you pick a player who never plays in the NHL game at the beginning of the first round of a great draft year, you dropped the ball. And you get punished for it. Older mistakes punish you more because, as time passes, the potential of that draft grows (other players accumulate game played and points) while your bad pick stays at zero. In my first ranking I had Winnipeg, Atlanta, Arizona and Phoenix. The older "teams" Atlanta and Phoenix were at the bottom and the newer "teams" were at the top. That is because older picks are more punishing. So you have to have teams with similar number of picks over the same period of time to compare. I fixed that by replacing those team names to Coyotes and Winnitlanta.

This rating, I think, removes some of the noise. As a head scout, you don’t control the timing between good draft years vs when your team sucks. You don’t control either when your GM decides to trade a first round pick. The proposed rating adjusts for that.

It does not however remove the countless other noise factors that head scouts don’t control.

  • You did pick one of the best players available but that player decides, three years later, that hockey is not that important to him. (Or that partying is equally important)

  • You have one of the best players available on your list but the GM likes that other big guy and forces you to pick him instead.

  • The coach, or the crowd, puts too much pressure too early on that gem you found and his confidence is destroyed.

  • Injuries, Development, Etc.

So is that ranking fair to Trevor Timmins?

Data hockdb.com drafts 2003-2016 as of 2021-11-11 Mean: 172

Rank

Team

Total Score

Total Potential

Num. picks

Scouting Rating

1

San Jose

23112

1042672

104

222

2

Pittsburgh

25429

1196971

95

212

3

Washington

26300

1272988

103

207

4

Boston

23179

1129507

95

205

5

Los Angeles

26537

1295524

109

205

6

Nashville

26012

1309509

116

199

7

Detroit

17799

898166

100

198

8

Toronto

18861

970807

100

194

9

Ottawa

22580

1164407

101

194

10

Anaheim

25627

1341031

99

191

11

Montreal

21887

1155462

99

189

12

St. Louis

25965

1432779

113

181

13

Buffalo

23005

1293662

114

178

14

Columbus

23999

1401782

111

171

15

Carolina

20229

1193619

100

169

16

Minnesota

18647

1117033

97

167

17

Chicago

24541

1493118

132

164

18

Tampa Bay

17886

1130164

110

158

19

Edmonton

22478

1425761

111

158

20

NY Islanders

22293

1430554

112

156

21

Philadelphia

17171

1119660

106

153

22

Colorado

17798

1168922

101

152

23

Dallas

18290

1227906

100

149

24

Coyotes

18742

1260204

102

149

25

Winnitlanta

17845

1223201

107

146

26

Vancouver

13043

899007

91

145

27

New Jersey

13311

954957

94

139

28

NY Rangers

17112

1277097

100

134

29

Florida

18941

1436674

111

132

30

Calgary

14213

1080473

99

132




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